def test_labels(self): x = np.arange(12).reshape((4, 3)) y = np.arange(8).reshape((4, 2)) ga = GaussianAugmentation() new_x, new_y = ga(x, y) self.assertTrue(new_x.shape[0] == new_y.shape[0] == 8) self.assertTrue(new_x.shape[1:] == x.shape[1:]) self.assertTrue(new_y.shape[1:] == y.shape[1:])
def test_labels(self): x = np.arange(12).reshape((4, 3)) y = np.arange(8).reshape((4, 2)) ga = GaussianAugmentation() x_new, new_y = ga(x, y) self.assertTrue(x_new.shape[0] == new_y.shape[0] == 8) self.assertEqual(x_new.shape[1:], x.shape[1:]) self.assertEqual(new_y.shape[1:], y.shape[1:])
def test_failure_augmentation_fit_predict(self): # Assert that value error is raised with self.assertRaises(ValueError) as context: _ = GaussianAugmentation(augmentation=True, apply_fit=True, apply_predict=True) self.assertTrue( 'If `augmentation` is `True`, then `apply_fit` must be `True` and `apply_predict`' ' must be `False`.' in str(context.exception)) if __name__ == '__main__': unittest.main()
def test_no_augmentation(self): x = np.arange(12).reshape((4, 3)) ga = GaussianAugmentation(augmentation=False) new_x, _ = ga(x) self.assertTrue(x.shape == new_x.shape) self.assertFalse((x == new_x).all())
def test_multiple_size(self): x = np.arange(12).reshape((4, 3)) ga = GaussianAugmentation(ratio=3.5) new_x, _ = ga(x) self.assertTrue(int(4.5 * x.shape[0]) == new_x.shape[0])
def test_double_size(self): x = np.arange(12).reshape((4, 3)) ga = GaussianAugmentation() new_x, _ = ga(x) self.assertTrue(new_x.shape[0] == 2 * x.shape[0])
def test_small_size(self): x = np.arange(15).reshape((5, 3)) ga = GaussianAugmentation(ratio=0.4) new_x, _ = ga(x) self.assertTrue(new_x.shape == (7, 3))
def test_no_augmentation(self): x = np.arange(12).reshape((4, 3)) ga = GaussianAugmentation(augmentation=False) x_new, _ = ga(x) self.assertEqual(x.shape, x_new.shape) self.assertFalse((x == x_new).all())
def test_multiple_size(self): x = np.arange(12).reshape((4, 3)) ga = GaussianAugmentation(ratio=3.5) x_new, _ = ga(x) self.assertEqual(int(4.5 * x.shape[0]), x_new.shape[0])
def test_double_size(self): x = np.arange(12).reshape((4, 3)) ga = GaussianAugmentation() x_new, _ = ga(x) self.assertEqual(x_new.shape[0], 2 * x.shape[0])
def test_small_size(self): x = np.arange(15).reshape((5, 3)) ga = GaussianAugmentation(ratio=0.4) x_new, _ = ga(x) self.assertEqual(x_new.shape, (7, 3))